Posted by Nodus Labs | January 6, 2014
The task of bibliographic synthesis can be significantly simplified using text network analysis. Visualization and graph analysis of a text corpus can provide very useful information about the overall topics present within and their interrelations. This can also make it much easier to find the most relevant topics at intersections of different texts’ subject fields and provide a map for building a concise overview of the text corpus.
Below is a graph visualization of the 15 articles presented in this case study. We processed each article using Textexture.Com text network analysis tool and created an aggregate graph from every article’s graph using Gephi. We then calculated standard graph metrics, such as betweenness centrality and modularity for every node. The bigger nodes on the graph are the ones that have higher betweenness centrality, which means that those nodes (words) appear more often at intersections between the distinct topics present within the text. Those are potentially interesting entrance points into the discourse as well. The nodes’ color indicates the community they belong to. Nodes of the same color are more densely connected together than with the rest of the network. These are the topics present within the texts, or the contexts that are covered by those 15 articles.
The resulting graph indicates:
1) The fact that all those articles are quite related to one another;
2) The different distinct topics that are explored in those 15 articles and their relation to one another;
3) The periphery of the graph show the areas where further questions may be asked;
4) The structural gaps in the graph also indicate the areas with the highest potential for further research;
These are the articles that we used:
Thompson, E., & Varela, F. J. (2001). Radical embodiment: neural dynamics and consciousness. Trends in cognitive sciences, 5(10), 418–425.
A seminal paper that proposes a more holistic point of view on body-mind-environment dynamics and consciousness. One of the main tenets of this study is that body plays an important role in constructing the meaning, and that representation does not only happen in the brain, but is a complex dynamical process that is dependent on the environment.
Basar, E. (2008). Oscillations in “brain–body–mind”—A holistic view including the autonomous system. Brain Research 1235. 2-11.
The authors show how oscillations in body and mind form the basis for cognition and interactions within the environment. Taking it one step further, they propose to incorporate the notion of “globally coupled oscillators” in order to gain new insights into the dynamics of nervous system.
Bystritsky, a, Nierenberg, a a, Feusner, J. D., & Rabinovich, M. (2012). Computational non-linear dynamical psychiatry: A new methodological paradigm for diagnosis and course of illness. Journal of psychiatric research, 46(4), 428–435.
In this paper the authors propose to use tools from non-linear dynamics to study behavior, emotional states and mental conditions. They demonstrate how this approach can be useful to better understand the complexity of interactions between the body, the mind, and the environment proposing its applications in psychotherapy.
D’Mello, S., Dale, R., & Graesser, A. (2011). Disequilibrium in the mind, disharmony in the body. Cognition & emotion, 00(00), 1–13. doi:10.1080/02699931.2011.575767
The authors found that small body movement fluctuation of individuals in cognitive equilibrium were characteristic of 1/f (pink) noise. When those individuals shifted into emotional distress, the whitening of the signal would occur. (white noise means there is no correlation between the frequency and the amplitude of a movement, pink noise is when there is such correlation – fractal scaling).
Yamada, N. (1995). Posture as a Dynamic Stable State of a Body. Research and Clinical Center for Child Development.
This very interesting study showed that the small natural movements of a standing body exhibits chaotic variability.
Nummenmaaa et al (2013). Bodily maps of emotions. PNAS
A great article that maps emotions onto the regions of human body, showing that there’s a statistically significant correlations between various a motions and the body parts where those emotions express themselves through (on the subjective level).
Micheloyannis, S., Pachou, E., Stam, C. J., Breakspear, M., Bitsios, P., Vourkas, M., … Zervakis, M. (2006). Small-world networks and disturbed functional connectivity in schizophrenia. Schizophrenia research, 87(1-3), 60–6.
In this paper the authors show how schizophrenia is associated with deviations in connectivity of functional cortical networks. Specifically, they show that small-world functional brain network connectivity usually associated with “healthy” behaviour is disturbed in schizophrenic patients. Which is an interesting finding, because the kind of dynamics that is possible in a network depends on its structure, so it could be that there’s something about the dynamics of small-world networks that we consider to be “healthy” (e.g. ability to segregate and integrate information from multiple sources).
Katerndahl, D., Ferrer, R., Best, R., & Wang, C.-P. (2007). Dynamic patterns in mood among newly diagnosed patients with major depressive episode or panic disorder and normal controls. Primary care companion to the Journal of clinical psychiatry, 9(3), 183–7.
This paper shows that mood shifts in healthy individuals follow circadian rhythms with chaotic variability, while the patients with depressive episodes and panic disorders have either circadian or chaotic variability overrepresented in their mood swings.
Mason, A (1990). Stereotypies: a critical review.
This paper shows how stereotypes (repetitive, invariant behaviour patterns with no obvious goal or function) typically occur in sub-optimal environments. Therefore, they can possibly be seen as symptoms for some kind of disturbance within the body-mind-environment system.
Frei, E., Gamma, a, Pascual-Marqui, R., Lehmann, D., Hell, D., & Vollenweider, F. X. (2001). Localization of MDMA-induced brain activity in healthy volunteers using low resolution brain electromagnetic tomography (LORETA). Human brain mapping, 14(3), 152–65.
This paper is interesting because it shows how MDMA affects various brain frequency bands and what behavioural and cognitive changes occur as a result of disturbed dynamics.
Manzano et al (2010) Thinking Outside a Less Intact Box: Thalamic Dopamine D2 Receptor Densities Are Negatively Related to Psychometric Creativity in Healthy Individuals
This paper shows a negative correlation between dopamine densities in thalamus and psychometric creativity scores. Would be interesting to see how specifically a change in dopamine density affects neural dynamics in different frequency bands.
Kyaga et al (2011) Creativity and mental disorder: family study of 300 000 people with severe mental disorder. The British Journal of Psychiatry.
This paper found a strong correlation between creativity and mental disorder in the study of 300000 Swedes. Could be an interesting point to start thinking what it is in creative work that helps so many people deal with disturbances in their mental well-being.
Lusebrink (2004). Art Therapy and the Brain: An Attempt to Understand the Underlying Processes of Art Expression in Therapy. Art Therapy: The Journal of American Art Therapy Association.
This paper attempts to lay out various strategies and techniques used in art therapy and to understand how they affect body-mind-environment dynamics in a way that’s beneficial for patients.